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Qwen · qwen3 · based on Qwen/Qwen3-4B-Base

Qwen3-4B

Qwen3-4B by Qwen: a 4B-parameter dense open-weight model under the apache-2.0 license with tool calling.

apache-2.0Dense41K contextTool callingReasoningAuto-imported · not yet reviewed

7,098,338 downloads · 704 likes · Model card · synced 2026-09-19

Specifications

Parameters
4B
Architecture
dense · qwen3
Layers
36
Hidden size
2,560
KV heads · head dim
8 · 128
Vocabulary
151,936
Native dtype
bfloat16
Context window
40,960 tokens
Released
2025-04-27
Last modified on Hub
2025-07-26

Features & licensing

License
apache-2.0
Commercial use
Yes
Modalities
text
Tool / function calling
Yes
Reasoning mode
Yes
Languages
EN
Quantised variants on Hub
FP8, GGUF
Pipeline
text-generation
transformerssafetensorsqwen3text-generationconversationaltext-generation-inferenceendpoints_compatible

Task fit

Editorial scores (0–100) used by the recommendation engine.

  • Chat70
  • RAG / Q&A70
  • Code70
  • Summarisation70
  • Extraction70
  • Agents70

Hardware to run Qwen3-4B

Weights need about 9 GB at FP16, 5 GB at INT8 and 3 GB at INT4. The KV cache adds roughly 147 MB per 1,000 tokens per request. For a reference workload of 5 requests per second with 1,500 input and 300 output tokens, total GPU memory is around 4.1 GB, which fits on 1 × NVIDIA A100 (80 GB).

GPU configurations at the reference workload
ConfigurationVRAMUtilisationEst. first tokenCloud / month
1 × NVIDIA L4 (24 GB)24 GB17 %~0.5 s$584
1 × NVIDIA L40S (48 GB)48 GB9 %~0.2 s$1,387
1 × NVIDIA A100 (80 GB)recommended80 GB5 %~0.1 s$2,336
1 × NVIDIA H100 (80 GB)80 GB5 %~0.0 s$3,285

Estimates only. Run an assessment for your own traffic.

Auto-imported from Hugging Face. Architecture, license and feature data are synced from the model repository; the task-fit scores below are provisional defaults until a curator reviews them.